Vectorized code refers to operations performed on multiple components of a vector at the same time. Vector or Single Instruction Multiple Data (SIMD) computing generally offers improved execution performance over scalar computing because it enables increased exploitation of the parallelism offered by vector or SIMD processors. However, Performance gains in valorization of loops in general purpose applications can be limited due to complex dynamic control flow. Compilers may not attempt to vectorize sparse branchy loops, especially when costly instructions such as gather and scatter are required for vectorization. For certain types of code, such as sparse and branchy loops, it is difficult to apply vectorization to achieve performance gains. What is needed, then, is an instruction to enable vectorization of certain types of code.